Summary: The bicuspid aortic valve (BAV) is the most common cardiac congenital anomaly and affects ~1.4% of the population, with an approximate 2:1 male predominance. Due to the widespread availability and routine use of screening echocardiography, the identification of asymptomatic young patients with BAV has become increasingly common. It has been estimated that 30%-50% of BAV patients will require surgical intervention at some point in their life (1). Surgery is most commonly required for calcific aortic valve disease (CAVD) that results in symptomatic aortic stenosis (AS); less commonly required for aortic insufficiency (AI), ascending aortic aneurysm, and dissection. In aortic valve replacement (AVR) patients under 50 years old having AS, virtually all of them have BAV. In fact, until the age of 70 BAV patients outnumber those with tricuspid aortic valve (TAV) having AVR for AS. Between 71-80 years of age BAV and TAV occur in approximately equal numbers in symptomatic AS patients, and not until over the age of 80 do TAV patients predominate (2). While multiple factors are likely involved in the prevalence of AS in BAV patients and its relation to aortic dissection, the presence of a BAV is consistently an exceptionally strong risk factor for premature AS. Yet, in spite of this strong clinical association it is not currently possible to assess which patients with BAV are at highest risk for developing AS, preventing a rational basis for BAV patient risk stratification. We thus hypothesize that sensitive, clinically derivable functional indices can be obtained from patient-specific dynamic BAV anatomy that, when combined with population-based leaflet properties, will yield clinically relevant patient-specific strategies for identifying BAV patients at high risk for developing symptomatic AS in the future. Narrative: The bicuspid aortic valve (BAV) is the most common cardiac congenital anomaly. Due to the widespread availability and routine use of screening echocardiography, development of clinical methods for the identification of asymptomatic young patients with BAV is now realistic. We thus plan to develop sensitive, clinically derivable functional indices that will yield clinically relevant patient- specific strategies for identifying BAV patients at high risk.